Two-Level Hierarchical Mission-Based Model Predictive Control

Justin P. Koeln, Andrew G. Alleyne

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A two-level hierarchical model predictive control (MPC) formulation is presented for constrained linear systems operating over a mission. Mission-based MPC is applicable to many control applications where the system operates for a finite time and stability about an equilibrium is not the primary objective. Instead, the primary control objective is to guarantee constraint satisfaction during operation as well as terminal constraints imposed on the final state of the system at the end of the mission. The secondary control objective is reference tracking, where references determine the desired operation for the system. A hierarchical control formulation permits the upper level controller to plan state trajectories over the entire mission, while a lower level controller modifies these trajectories to improve reference tracking. This decomposition of the control problem reduces computational cost, enabling real-time implementation for large systems with long missions. Feasibility proofs guarantee the constraint satisfaction while a numerical example demonstrates the efficacy of the approach.

Original languageEnglish (US)
Title of host publication2018 Annual American Control Conference, ACC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2332-2337
Number of pages6
ISBN (Print)9781538654286
DOIs
StatePublished - Aug 9 2018
Event2018 Annual American Control Conference, ACC 2018 - Milwauke, United States
Duration: Jun 27 2018Jun 29 2018

Publication series

NameProceedings of the American Control Conference
Volume2018-June
ISSN (Print)0743-1619

Other

Other2018 Annual American Control Conference, ACC 2018
CountryUnited States
CityMilwauke
Period6/27/186/29/18

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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